Triple
T8945285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accrington |
E213205
|
entity |
| Predicate | brickTypeCharacteristics |
P23657
|
FINISHED |
| Object | very hard engineering brick |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: very hard engineering brick | Statement: [Accrington, brickTypeCharacteristics, very hard engineering brick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brickTypeCharacteristics Context triple: [Accrington, brickTypeCharacteristics, very hard engineering brick]
-
A.
cementType
Indicates the specific kind or classification of cement associated with an entity.
-
B.
constructionCharacteristic
chosen
Indicates a specific structural or material property that characterizes how something is built or constructed.
-
C.
streetMaterial
Indicates the material composition from which a street or road surface is made.
-
D.
stoneColor
Indicates that one entity has a particular color attribute associated with a stone.
-
E.
wallMaterial
Indicates that one entity is the material from which a wall or walls of another entity are constructed.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66db998c8190999a7a686bbdda1f |
completed | April 1, 2026, 12:29 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:59 p.m.